Clinical Sensitivity of Sub-millimetre-resolution Definite Versus Thin Inter-/Intramuscular Fat Streaks from Calf and Thigh MRI.

Kenneth Tam, Si Wen Liu, Sarah Costa Ianes, Eva Szabo, Shannon Reitsma, Hana Gillick, Jonathan D Adachi, Andy Kin On Wong

Abstract read

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In one paragraph

Article in Calcified tissue international, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Kenneth TamDepartment of Neurobiology, Physiology, and Behavior, University of California Davis, Davis, CA, USA.

Si Wen LiuRehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada.

Sarah Costa IanesJoint Department of Medical Imaging, University Health Network, Toronto General Hospital Research Institute, 200 Elizabeth St. 7EN-240, Toronto, ON, M5G2C4, Canada.

Eva SzaboJoint Department of Medical Imaging, University Health Network, Toronto General Hospital Research Institute, 200 Elizabeth St. 7EN-240, Toronto, ON, M5G2C4, Canada.

Shannon ReitsmaDepartment of Medicine, McMaster University, Hamilton, ON, Canada.

Hana GillickDepartment of Medicine, McMaster University, Hamilton, ON, Canada.

Jonathan D AdachiDepartment of Medicine, McMaster University, Hamilton, ON, Canada.

Andy Kin On WongRehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada. andy.wong@uhn.ca.ORCID http://orcid.org/0000-0001-8540-8854

Funding

Arthritis Society 21-0035Institute of Musculoskeletal Health and Arthritis MOP-115094Institute of Musculoskeletal Health and Arthritis PJT-156274Institute of Musculoskeletal Health and Arthritis PJT-166012

6 · The paper itself

Abstract

Sub-millimetre resolution magnetic resonance imaging (MRI) reveal detailed patterns of inter- and intra-muscular fat (IMF) enabled by recent segmentation algorithms. However, clinical relevance of finer IMF streaks, beyond definite deposits, remains unclear. T1-weighted spin-echo MRI was acquired in the AMBERS (Appendicular Muscle and Bone Extension Research Study; calves from community-based females) and OAI (Osteoarthritis Initiative; thighs from disease-focused males and females) cohorts, including adults 45-85 years old. Thigh and calf MR images were segmented using the iterative threshold-seeking algorithm to quantify definite versus thinner streaks, with 3D connectivity verification, and partial volume correction. Absolute and relative IMF volumes were derived. Lower-extremity physical function and activities of daily living (ADL) were assessed contemporaneously. Clinical sensitivity was evaluated using multivariable linear regression relating IMF volumes to demographics, physical function, and ADLs. Among 385 adults (89% female; age 71.6 ± 7.6 years; body mass index (BMI) 28.1 ± 4.9 kg/m

Indexed as

Adipose TissueLegMagnetic Resonance ImagingMuscle, SkeletalThighActivities of Daily LivingAgedAged, 80 and overFemaleHumansMaleMiddle AgedActivities of daily livingAutomatedClinical sensitivityFat streaksInter- and intramuscular fatMRIMuscle fatPhysical functionSegmentationThinner streaks

Identifiers

PMID42142126

DOI10.1016/j.jot.2023.07.005

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.